Speakers in the public record
Claim mix
belief 15recommendation 4prediction 4evaluation 3uncertainty 1commitment 1preference 1
Evidence policy
Every row below preserves an exact excerpt. Identified speakers are linked; unresolved voices are labeled and excluded from people counts.
Claim ledger
The useful parts, with receipts.
29 published records
“At work? It's probably Thinking Machines, so it's all about treating the cause, not the symptoms. The prototypical example is if you want to solve traffic, you don't actually put up speed bumps or speed limits, you actually have to solve walkability and mobility and why people actually use cars. Outside of that, personally, the CMO of Instacart recommended to me Tomorrow, and tomorrow, and tomorrow and I read it last month and last year and the year before because I love it so much. It's like this beautiful story over 10 years.”
- Publisher
- Lenny's Podcast
“There's certainly going to be a bunch of new things to learn if that world ever plays out, but I think managing devices and policies and group access, all those things are solved problems, which is good.”
- Publisher
- Lenny's Podcast
“We touched on it a little bit, but I think that with the advent of agents and products that think and can act and reason, there's going to be this new wave around RL and I have a deep belief that that will become one of the most important product techniques of the next season or at least the next few seasons.”
- Publisher
- Lenny's Podcast
“I think that Manus breakthrough in the space was that they could do these tool calling loops and have agents do longer running tasks that really no other platform was able to do. I think stuff like that is critical.”
- Publisher
- Lenny's Podcast
“I think we're all early in this journey and great platforms that are built on great use cases and built on great customers, and so if you have feedback, you have ideas, you have things want AI to be able to do to help you achieve more, I'd love to hear it.”
- Publisher
- Lenny's Podcast
“I don't know where we're going with that, but that was like, now you're like, yeah.”
- Publisher
- Lenny's Podcast
“Look, I think that software as a primitive is changing and the artifact inside of it is a model alongside the software components itself.”
- Publisher
- Lenny's Podcast
“I think about an ensemble of models as a set of multiple models that then you can fine-tune and deploy independently, but at this point, we're all making up different terminology to define things that we have deep beliefs on that have limited sets of data points because everything is moving so fast.”
- Publisher
- Lenny's Podcast
“I just think that the reason why terminals are great and it feels really great when you code is because of the way it can interact with an LLM with the text stream. And I think that both can be true that humans will continue to commit code and will find new ways to actually do that, whether it's in the IDE, whether it's in GitHub, Copilot, whether it's in some new development environment, and I think that we'll do that with agents and agents will do that with each other and we'll continue to evolve from there.”
- Publisher
- Lenny's Podcast
“How do you observe if they, it's doing the right thing, how do you fine-tune it if they're not, all of those things. So I think that I'm just speculating that there's a world in which that could be pretty exciting and I think that's great because we can just accomplish more.”
- Publisher
- Lenny's Podcast
“As of this year, Nathan Lambert did this study that I thought was pretty interesting of all the top leader boards and it showed that once a model hits 30 billion parameters, the CapEx to actually train a model and put billions of tokens into a pre-run doesn't economically make sense and you can start to optimize on the loop. And so yeah, in many ways, I think using your own data is the best way to do that, but you can synthetically generate data.”
- Publisher
- Lenny's Podcast
“I 100% believe that's where the world is going, and then my experience should look and feel different than yours.”
- Publisher
- Lenny's Podcast
“We all choose to someone who just said this to me and I thought it was great, "We all choose to close the door on our kids every single day to go work on something." And so you have to work on something that is deeply moving to you and you have a deep belief that is going to make the world a better place and I think that's why it's vibes.”
- Publisher
- Lenny's Podcast
“Oh, it's just going back to our previous discussion on the signals loop and products evolving and becoming these living organisms and not these artifacts. And if you think about getting really good at that loop, I think that is the product, that is the IP, that is the future of every organization and I think feedback becomes continuous and observability becomes the culture, and I think that functions start to blur in future workforces.”
- Publisher
- Lenny's Podcast
“I think we have this conviction on a set of building blocks that we want to provide to enable these agents to endure and have high endurance and so that's what we're focused on.”
- Publisher
- Lenny's Podcast
“With this explosion of models that we talked about in the beginning, there's a lot of good models to choose from for different domains. And so I think that you just get more leverage economically, you get more leverage from a taste perspective of how you actually want to steer a model if you're actually doing reinforcement learning or some sort of fine-tuning to actually start to optimize what's off the shelf for some outcome like price, performance, quality.”
- Publisher
- Lenny's Podcast
“I believe we will see just as much money spent on post-training as we will on pre-training and in the future, more on post-training.”
- Publisher
- Lenny's Podcast
“I think the beauty is there's a lot of models that can help you achieve that, and so I'm much more in the model system rather than one model to rule them all.”
- Publisher
- Lenny's Podcast
“We think about it as what season are we in? Season one might've been prototyping of AI and then it was all around models and reasoning models, and now it's the advent of agents.”
- Publisher
- Lenny's Podcast
“I think that some of the most consequential products in the world required a bunch of deterministic, logical sets of inputs and sparks of creativity and imagination and judgment and vision that could not be achieved without humans.”
- Publisher
- Lenny's Podcast
“Every company should be bringing AI to where their users are and ChatGPT has all of their users using chat and it's a phenomenal product and we've got lots of people around the world that do work in many different ways and we should be thinking about how we use AI to enable that.”
- Publisher
- Lenny's Podcast
“" And it makes me think about something else of just you would think why can't just GPT-5 build its own user interface just like as you use it, it just evolve. It's sort of what it's doing with Canvas and all these things, but that's another way I think about when you talk about this idea of product as organism is the product, the UX can shift based on how you're using it and evolve automatically without having product teams have to do anything.”
- Publisher
- Lenny's Podcast
“At this point, we have AI and agents and many of our workflows, one of my favorite ones, so right now are my engineering partners out. So I jump on the live site bridges when something goes down and as something as simple as you can automatically get a summary of everything that just happened because usually, there's 15 people talking, you don't actually know where the incident started, where it's going to end and everything and then all of a sudden I have that and I can figure out and ask questions and get updates.”
- Publisher
- Lenny's Podcast
“It's really hard to know which one you should use for what outcome. And so you really need to bet on a platform or some app server type layer that allows you to swap things in and out and not really be beholden to anything, any one technology or any one tool because the reality is the whole thing is going to change.”
- Publisher
- Lenny's Podcast
“It's been a pretty interesting shift, especially over the last year or so because when I got to Microsoft, it was right after OpenAI and the large foundation models happened, and then immediately after there was this explosion of models, proprietary open frontier models that were pushing the frontier curve and so they were both more efficient and then we're starting to see domain level expertise in a bunch of them and then even more recently, models now can tool call and they can function call and they can take action, and I think that's just giving way to a new type of products that are starting to see some success.”
- Publisher
- Lenny's Podcast
“Because these models are so effective at this point, you want to start to tune them to certain types of outcomes.”
- Publisher
- Lenny's Podcast
“You don't have to trade that off of working extra hours or the importance of family and all of those things. And so I think that my worldview is when I'm 70, it's not about what do I look back on in my life and count the number of regrets, it's really about looking forward in the number of adventures I will still have because I have accumulated this wealth of skills and trust and people and family and impact and things like that.”
- Publisher
- Lenny's Podcast
“I think that for the average employee, my hope and my optimistic view is that they will be able to expand their skill set because now they have their own agents stack that they can bring with them to work just like you can bring your own device and you can start to have access to a set of skills that you never had before.”
- Publisher
- Lenny's Podcast
“I want to start with something that we were chatting about before this that I've never heard about as a concept that I think is going to be really helpful for people to think about, which is this concept you have that we're moving from product as artifact to product as organism.”
- Publisher
- Lenny's Podcast